Skip to main content
ticket-rs is built for a specific use case: AI agents and developers who live in the terminal. Here’s how it compares to alternatives.

​
Feature Comparison

Featureticket-rsBeadsJIRA/LinearGitHub Issues
Git-backed✅ Markdown + YAML✅ SQLite + git❌ Cloud database❌ Cloud database
Dependencies✅ Built-in graph✅ Built-in⚠️ Limited❌ None
Graph Analytics✅ PageRank, critical path⚠️ Basic❌ None❌ None
AI-Native✅ MCP, hooks, triage✅ Good CLI⚠️ API only⚠️ API only
Offline Mode✅ Full functionality✅ Full functionality❌ Requires network❌ Requires network
Background Process✅ None (stateless)❌ SQLite daemon❌ Browser required❌ Browser required
Installation✅ Single binary⚠️ Go + SQLite❌ Browser only❌ Browser only
External Sync✅ GitHub, Linear❌ NoneN/A (is the system)N/A (is the system)
Sandboxed Env✅ Works everywhere⚠️ Needs SQLite❌ API tokens❌ API tokens
Merge Conflicts✅ Rare (text files)❌ SQLite conflictsN/AN/A
Team UI⚠️ CLI + sync❌ CLI only✅ Rich web UI✅ GitHub UI
Speed✅ Rust performance✅ Go performance⚠️ Network latency⚠️ Network latency

​
Performance Benchmarks

We maintain a comprehensive benchmark suite comparing ticket-rs against alternative implementations including bash scripts and Go-based tools (beads). All benchmarks are automated and run with Monte Carlo analysis across multiple dataset sizes.

​
Benchmark Results

Overall Performance (median across all commands, 500 tickets, 30 iterations). This is the same canonical dataset that powers the chart on the about page and is regenerated from the benchmark suite:
Benchmarks run with 500 tickets, 30 iterations. Data source: benchmark-data.json
Key Findings:

Rust CLI Speed

Fastest overall — ~4× faster than bash and 6.2× faster than the Go daemon, with no dependencies and instant startup.

PyO3 Bindings

Zero subprocess overhead for Python-first workflows: in-process Rust via PyO3, no per-call process spawn.

Linear Scaling

O(n) complexity with excellent constants. Handles 1,000+ issues efficiently.

​
Detailed Command Performance

Operations tested: ready, list, show, stats, create, update Highlights (Rust CLI, 500-ticket dataset):
  • Ready command: Finds unblocked issues in ~4.5ms (vs ~35ms in bash)
  • List command: Full issue list in ~14ms (vs ~35ms in bash)
  • Show command: Single issue lookup in ~4ms (vs ~39ms in bash)
  • Stats command: Repository stats in ~14ms
Per-command latency scales with dataset size — the numbers above are at 500 tickets. On smaller repositories (and for the CLI’s own regression suite) these commands run in the low single-digit milliseconds.

​
Scaling Analysis

Tested with 10, 50, 100, 500, and 1,000 ticket datasets:
  • ticket-rs/ticket-py: O(n) scaling with minimal overhead
  • bash: O(n²) for operations requiring full repository scans
  • beads daemon: Constant daemon overhead + O(n) parsing
View full benchmark methodology, charts, and raw data in pypi/benchmarks/BENCHMARK_REPORT.md

​
When to Use ticket-rs

ticket-rs is ideal when you:
Work primarily in the terminal and IDE
Use AI coding assistants (Claude, Cursor, Windsurf)
Want git-backed issue tracking that versions with code
Need dependency graphs and smart prioritization
Value offline capability and zero external dependencies
Work in sandboxed environments (CI/CD, containers)
Want blazing fast commands (milliseconds, not seconds)

​
When NOT to Use ticket-rs

Consider alternatives when you:
Need rich web UI — JIRA/Linear have comprehensive dashboards, Gantt charts, reporting
Non-technical team — PMs and designers may prefer visual interfaces (though you can sync externally)
Massive scale — Optimized for <10k issues per repo; use dedicated systems for millions of issues
Real-time collaboration — No live updates; use git push/pull for sync

​
Detailed Comparisons

​
vs. Beads

Beads pioneered AI-native issue tracking. ticket-rs builds on those ideas:
  • ✅ Git-backed storage
  • ✅ Dependency tracking
  • ✅ AI-native CLI
  • ✅ Terminal-first workflow

​
vs. JIRA / Linear

JIRA and Linear are full-featured project management systems. ticket-rs is developer-focused.
  • Team needs rich web UI
  • Non-technical stakeholders
  • Complex workflows (sprints, epics, boards)
  • Advanced reporting and dashboards
  • Real-time collaboration
You can have both: Use ticket-rs for your workflow, sync to JIRA/Linear for team visibility.

​
vs. GitHub Issues

GitHub Issues is tightly integrated with GitHub. ticket-rs is git-native.
  • Built into GitHub (no separate tool)
  • Rich web UI
  • Integrations with Actions, Projects
  • Team-friendly interface

​
vs. Plain Text / Markdown Files

Some teams just use TODO.md or NOTES.md. ticket-rs adds structure:

​
Migration Guides

Switching to ticket-rs is straightforward:

From Beads

Auto-converts SQLite to markdown

From GitHub

Imports existing issues

From Linear

Bidirectional sync

​
Next Steps

Quickstart

Install ticket-rs and try it out

Philosophy

Understand our design principles

Graph Analytics

Learn about tk’s killer feature

GitHub

Star the repo and contribute